Wood products, such as logs, boards, other lumber products, or the like, can be graded or classified into qualitative groups by the amount of warp potential, or dimensional stability, in the product. Crook, bow, twist, and cup are examples of warp and are illustrated in FIG. 1. The groups are used to qualitatively represent the warp state at a specified ambient condition or the degree of warp instability of a wood product. The qualitative groups are typically ordinal in nature, though nominal categories may also be used.
Examples of qualitative estimates of warp might be, but are not limited to, low crook, high crook, crook less than 0.5 inches but greater than 0.25 inches, medium bow, bow greater than 1 inch, or like estimates. It might be desirable to classify the warp distortion that a wood product will undergo after it is remanufactured, its moisture redistributes, or it is placed in a new relative humidity environment. Examples of these classifications might be, but are not limited to, low crook at 20% RH, medium crook at 65% RH, high bow at 90% RH, crook greater than 0.5 inches at 20% RH. Wood products can also be characterized in a quantitative manner, such as, an amount of change a wood product will undergo (i.e., crook equal to 0.25 inches). Several known methods for determining quantitative estimates are described below.
The degree of warp depends on several known factors, such as density, modulus of elasticity (hereinafter referred to as “MOE”), moisture content variation, pith location, compression wood, grain angle and others. Many of these factors can be quantitatively or qualitatively evaluated with different types of sensors. For example, MOE can be estimated from the propagation of sound through wood, and specific gravity can be estimated from the capacitance of wood. A different type of sensor group or system may be utilized for detecting each of these properties.
During the three year period from 1995 to 1998, solid sawn softwood lumber usage in wall framing, floor framing and roof framing dropped by 9.9%, 17.2% and 11% respectively in the United States (Eastin et al., 2001)1. In this survey of nearly 300 builders, lumber straightness was rated the most important factor affecting buying decisions; yet of all the quality attributes surveyed, dissatisfaction with straightness was highest. It is generally recognized that softwood lumber will continue to lose market share unless the industry improves the in-service warp stability of its product. 1Eastin, I. L., Shook, S. R., Fleishman, S. J., Material substitution in the U.S. residential construction industry, 1994 versus 1988, Forest Products Journal, Vol. 51, No. 9, 31-37.
Some wood product applications are intolerant of significant dimensional change (thickness, width, length) after the product is put in service. For example, instability of thickness or width dimensions can cause interference problems for tight-tolerance applications, such as doors and windows. Length instability of wood used in truss chords can result in a problem known as truss uplift; where the truss can raise above interior wall plates forming a gap between the ceiling and interior wall.
In the United States, most softwood dimension lumber is visually graded for a variety of attributes that affect its appearance and structural properties. These attributes include knots, wane, dimension (thickness, width, and length), decay, splits and checks, slope-of-grain, and straightness (warp). Strict quality control practices overseen by third party grading agencies are in place to ensure that all lumber is “on-grade” at the point the grade is assigned. Unfortunately, the straightness and dimension of a piece are not static and can change after the piece is graded. Additional warp and size change can develop after the piece is in the distribution channel or after it is put into service. Typical moisture content of fresh kiln dried lumber averages 15% but ranges from 6% to 19%. This lumber will eventually equilibrate to a moisture ranging from 3% to 19% depending on time of year, geography and whether the application is interior or exterior (Wood Handbook)2. This moisture change results in changes in both dimension and warp properties. Any piece of lumber is prone to develop additional “in-service” warp if a) its shrinkage properties are not uniform and it changes moisture or b) its moisture content is not uniform at the point the original grade was assigned. Neither of these conditions is detectable with traditional visual grading methods. Customers of wood products seek stability in both dimension and warp properties. 2Wood Handbook, General Technical Report 113 (1999) Department of Agriculture, Forest Service, Forest Products Laboratory.
The wood handbook2 provides guidelines for assessing the width and thickness stability of solid sawn lumber. Average thickness and width shrinkage is governed by grain orientation as well as radial and tangential shrinkage properties. These average radial and tangential shrinkage values vary by species and are reduced if heartwood is present. Although these methods can be used to estimate the average thickness and width shrinkage behaviour of a species, methods for precise quantification do not exist. There are even fewer design tools for estimating length shrinkage.
A number of studies (e.g. Johansson, 20023 and Beard et al., 19934) have attempted to define visual indicators that correlate with warp stability. Candidate indicators have included features such as percent juvenilewood, grain orientation, compressionwood, pith location, wane, knot properties and growth rate. Although these studies demonstrate that spiral grain can be a useful predictor of twist stability, they generally agree that there are no reliable visual indicators of crook and bow stability. 3Johansson, M., and Kliger, R., Influence of material characteristics on warp in Norway Spruce studs, Wood and Fiber Science. 34(2). 2002. pp 325-336, 2002 by the Society of Wood Science and Technology 4Beard, J. S., Wagner, F. G., Taylor, F. W., Seale, R. D., The influence of growth characteristics on warp in two structural grades of southern pine lumber, Forest Products Journal, Vol. 43, No. 6, pp 51-56.
Several theoretical models have also been developed to help explain how moisture and various wood properties interact to cause distortion. Nearly fifty years ago, a mathematical model was developed to explain lumber twist as a function of spiral grain angle, distance from pith, and rate of tangential shrinkage during moisture loss (Stevens et al., 19605). Other recent work has sought to develop finite element models to predict crook and bow distortion (Ormarsson et al., 19986) as a function of three-dimensional patterns of density, growth rings, moisture, modulus of elasticity, etc. Another finite element model is described in a series of U.S. Pat. Nos. 6,308,571; 6,305,224; and 6,293,152 to Stanish et al. All of these models teach that the fundamental cause of lumber warp is related to the fact that it shrinks significantly when it dries and this shrinkage is both anisotropic and highly non-uniform. Prediction of warp stability of a wood product is made even more difficult by the fact that its moisture content changes with the vapour pressure of the surrounding environment and this “equilibrium moisture” can be highly variable between two locations within a piece depending on the chemistry and fibre differences between those two locations. 5Stevens, W. C., and Johnston, D. D., Distortion caused by spiralled grain, Timber Technology, June 1960, pp 217-218.6Ormarsson, S., Dahlblom, O., Petersson, H., A numerical study of the shape stability of sawn timber subjected to moisture variation, Wood Science and Technology 32 (1988) 325-334, Springer-Verlag 1998.
Today the patterns of equilibrium moisture and shrinkage coefficients within a full size lumber product can be accurately measured only in a laboratory environment. The laboratory technique involves cutting the piece of lumber into small “coupons” and measuring the moisture content and shrinkage coefficients using ASTM standards D-4492 and D-143, respectively. Although much is known about equilibrium moisture and shrinkage behaviour of wood, there are as yet no comprehensive theoretical models and no methods of monitoring these properties in a real time production environment.
Much of the fundamental research to develop shrinkage models for wood was done several decades ago. Shrinkage is known to be related to microfibril angle (Meylan, 19687). This relationship is best where microfibril angle is in the range of 30° to 40° and outside this range, the relationship is rather poor. Wooten (Wooten, 19678) observed that longitudinal shrinkage of high microfibril angle wood (>40 degrees) in seedlings seemed to correlate with the thickness of the S1 layer—although no data was presented. Cave (Cave, 19729) proposed a shrinkage theory which includes effects of the S1 layer. More recently, Floyd (Floyd, 200510) demonstrated that certain hemicellulose components, particularly galactan, interact with microfibrils to affect longitudinal shrinkage rates. This combined work suggests that measurements relating to microfibril angle and wood hemicellulose chemistry should be useful in predicting shrinkage patterns in wood. 7Meylan, B. A., Cause of high longitudinal shrinkage in wood, Forest Products Journal, Vol. 18, No. 4, April 1968, pp 75-78.8Wooten, T. E., Barefoot, A. C., and Nicholas, D. D., The longitudinal shrinkage of compression wood, Holzforschung, Bd. 21 (1967), Heft 6, pp 168-171.9Cave, I. D., A theory of the shrinkage of wood. Wood Sci. Tech (1972), 6:284-292.10Floyd, S. “Effect of Hemicellulose on Longitudinal Shrinkage in Wood.” In The Hemicellulloses Workshop 2005: WQI Limited—New Knowledge in Wood Quality. Conference held in The Wood Technology Research Centre. University of Canterbury, New Zealand, 10-12 Jan. 2005, edited by Kenneth M. Entwistle and John C. F. Walker, 115-. Christchurch, New Zealand, 2005.
Several researchers have recently reported some success using these approaches to estimate shrinkage properties. The above referenced patents issued to Stanish et al. teach a method of inferring shrinkage behaviour by interpreting patterns of acoustic or ultrasound propagation velocity (related to microfibril angle). Several recent patents and publications have begun to disclose methods of estimating shrinkage coefficients which are more compatible with a high speed lumber manufacturing process. For example, Nystom (Nystrom et al.11) demonstrated the relationship between longitudinal shrinkage and an optical property of wood (“tracheid-effect”) that is also related to microfibril angle. The “tracheid effect” is taught in U.S. Pat. No. 3,976,384 issued to Matthews et al. A large number of recent publications and patents (e.g. Kelley et al.12) teach a method 11Nystrom, J.; Hagman, O.; Methods for detecting compression wood in green and dry conditions., Proceedings of the SPIE—The International Society for Optical Engineering (1999) vol. 3826, p. 287-94.12Kelly, S.; Rials, T.; Snell, R.; Groom, L.; Sluiter, A; Wood Science and Technology (2004), 38(4), 257-276. of inferring shrinkage properties by using chemometric methods of near infrared spectroscopy (NIRS). NIRS is of particular interest because the method is sensitive to both physical attributes of the fibres (e.g. microfibrils) and chemical attributes (e.g. hemicellulose).
Unfortunately, none of the individual methods described above are accurate enough to give adequate estimates of the dimensional stability of a single piece of lumber. Thus, a need exists for the use of single or multiple sensor systems to provide a qualitative and/or quantitative estimate of the current or future warp distortion of the wood product or of warp-related properties of the wood product.